Parallel computation is a method used to reduce simulation turnaround time. Computational domain decomposition into smaller processing units is the common practice of dividing a computational load among processors in parallel computations, such as those currently practiced in various simulations. As expected, with certain limitations (e.g., Amdahl's law, faster networks, load imbalance, etc.), simulation turnaround time is likely to decrease as more and more processors are added for a given simulation task for a computational domain. While load imbalance among processors can be a result of non-optimal decomposition of the computational domain, load imbalance can also be a result of faulty hardware (node) on the computational platform, even though a particular computational algorithm may be perfectly balanced for execution on each of a plurality of parallel-processing processors associated with a node. The use of a faulty node in a parallel computation can result in, among other things, performance degradation, slowdown of a simulation, erroneous data, business inefficiency, loss of revenue, user dissatisfaction, and/or an increase in a total cost of ownership for a simulation/simulation system.